denial-of-service attack

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denial-of-service attack

An assault on a network that floods it with so many requests that regular traffic is either slowed or completely interrupted. Unlike a virus or worm, which can cause severe damage to databases, a denial of service attack interrupts network service for some period.

Distributed Attack
A distributed denial-of-service (DDOS) attack can employ hundreds or even thousands of computers that have been previously infected. The computers act as a network of "zombies" working together to send out bogus messages, thereby creating huge volumes of phony traffic.

In 2016, the Dyn DNS system was hammered by a DDOS attack that caused sporadic slowdowns of major sites such as Twitter, Netflix and The New York Times. The zombie traffic reached more than 100 gigabytes per second of bogus messages. See botnet, smurf attack, SYN flood attack, land attack, teardrop attack and Ping of Death.

It's Not a New Phenomenon
In February 2000, computers were activated that had been previously hacked and planted with illicit programs. The unending number of requests caused a denial of service at Yahoo!, eBay, and other websites. (Article headline courtesy of the Philadelphia Inquirer.)
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References in periodicals archive ?
Another kind of source-side detection method is threshold based detection, which is one of the most practical methods to deal with DoS attack from both source-side and victim-side [1, 4, 24].
4.2 CUSUM chart detection of DoS attack based on the UDP and ICMP packets concurrently.
Annette Lagman, UP said the SAIS 'has long been secured from any DoS attack from known overseas attackers, but was configured to treat traffic coming from the Philippines as valid and not hostile.'
This helps to identify the neighbor nodes that are DOS attack nodes and they can be eliminated.
This second case study implements a workflow-based scenario to simulate the effect of a DoS attack and a phishing attack on an online course management system established for testing.
Their scheme is vulnerable to the masquerade attack, smart card attack, user impersonation attack, and DoS attack and does not achieve perfect forward secrecy.
This section presents simulation result of "priority based approach" when compared with normal AODV, DoS attack, and game theory (Table 7).
[10] studied the Gossamer protocol for the prevention of DoS attacks by de-synchronization on RFID systems.
[20] proposed a location-aware-end-to-end security framework which is robust against DoS attack. It uses efficient en-route false data filtering scheme in order to identify the false data injection attack.
Most common model types used for DoS attack modelling are mentioned to show why we suggest using mathematical models and what models have already been proposed to be used for modelling different types of DoS attacks.